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def initialize_prom_client(distribution, prometheus_url, prometheus_bearer_token):
global prom_cli
(prometheus_url, prometheus_bearer_token) = instance(distribution, prometheus_url, prometheus_bearer_token)
if (prometheus_url and prometheus_bearer_token):
bearer = ('Bearer ' + prometheus_bearer_toke... |
def disable_import(prefix):
realimport = builtins.__import__
def my_import(name, *args, **kwargs):
if name.startswith(prefix):
raise ImportError
return realimport(name, *args, **kwargs)
try:
builtins.__import__ = my_import
(yield)
finally:
builtins.__i... |
class Explara(object):
def __init__(self, access_token):
self.access_token = access_token
self.headers = {'Authorization': ('Bearer ' + self.access_token)}
self.base_url = '
def get_events(self):
events = requests.post(self.base_url.format('get-all-events'), headers=self.headers)... |
def test_fixtures_nose_setup_issue8394(pytester: Pytester) -> None:
pytester.makepyfile('\n def setup_module():\n pass\n\n def teardown_module():\n pass\n\n def setup_function(func):\n pass\n\n def teardown_function(func):\n pass\n\n def... |
def add_new_params(old_grid, new_grid, old_name, new_name):
if new_grid:
new_params = set(new_grid.keys())
old_params = set(old_grid.keys())
if (len(old_params.intersection(new_params)) > 0):
raise ValueError('Overlap in parameters between {} and {} of the chosen pipeline.'.forma... |
.usefixtures('session_app_data')
def test_pick_periodic_update(tmp_path, mocker, for_py_version):
(embed, current) = (get_embed_wheel('setuptools', '3.6'), get_embed_wheel('setuptools', for_py_version))
mocker.patch('virtualenv.seed.wheels.bundle.load_embed_wheel', return_value=embed)
completed = (datetime.... |
def get_time_display(prev_record: Optional[Record], record: Record) -> Tuple[(str, str, str)]:
time_absolute = record.timestamp.isoformat()
time_color = ''
if prev_record:
(time_display, delta_seconds) = nice_time_diff(prev_record.timestamp, record.timestamp)
if (delta_seconds <= 10):
... |
class Effect5870(BaseEffect):
type = 'passive'
def handler(fit, ship, context, projectionRange, **kwargs):
fit.modules.filteredItemBoost((lambda mod: mod.item.requiresSkill('Shield Operation')), 'shieldBonus', ship.getModifiedItemAttr('shipBonusCI2'), skill='Caldari Hauler', **kwargs) |
def get_total_memory(unit='G', number_only=False, init_pid=None):
from pyrl.utils.data import num_to_str
if (init_pid is None):
init_pid = os.getpid()
process = psutil.Process(init_pid)
ret = process.memory_full_info().uss
for proc in process.children():
process_info = proc.memory_fu... |
def test_indent(caplog):
caplog.set_level(logging.INFO)
lg = logger.copy()
nesting = lg.nesting
name = uniqstr()
with lg.indent():
lg.report('make', name)
assert any((match_report(r, activity='make', content=name, spacing=(ReportFormatter.SPACING * (nesting + 2))) for r in caplog.records... |
def first_stage():
ql = Qiling(['rootfs/8086/doogie/doogie.DOS_MBR'], 'rootfs/8086', console=False)
ql.add_fs_mapper(128, QlDisk('rootfs/8086/doogie/doogie.DOS_MBR', 128))
ql.os.set_api((26, 4), set_required_datetime, QL_INTERCEPT.EXIT)
hk = ql.hook_code(stop, begin=32792, end=32792)
ql.run()
ql... |
def _toWindowsPath(p):
pp = p.split('/')
if (getFoamRuntime() == 'BashWSL'):
if p.startswith('/mnt/'):
return ((pp[2].toupper() + ':\\') + '\\'.join(pp[3:]))
else:
return p.replace('/', '\\')
elif (getFoamRuntime() == 'BlueCFD'):
if p.startswith('/home/ofuser/... |
def _check_resultsets_equal(res1, res2):
try:
assert np.allclose(res1.species, res2.species)
except ValueError:
pass
assert np.allclose(res1.tout, res2.tout)
assert np.allclose(res1.param_values, res2.param_values)
if isinstance(res1.initials, np.ndarray):
assert np.allclose(... |
def download_file(url, path):
print('Downloading: {} (into {})'.format(url, path))
progress = [0, 0]
def report(count, size, total):
progress[0] = (count * size)
if ((progress[0] - progress[1]) > 1000000):
progress[1] = progress[0]
print('Downloaded {:,}/{:,} ...'.for... |
class ViewRecords(db.Model, AuditTimeMixin):
__tablename__ = 'tb_view_record'
id = db.Column(db.Integer, primary_key=True)
domain_name = db.Column(db.String(256), nullable=False)
record = db.Column(db.String(256), nullable=False)
record_type = db.Column(db.String(32), nullable=False)
ttl = db.Co... |
class Migration(migrations.Migration):
dependencies = [('proposals', '0027_auto__0540')]
operations = [migrations.AlterField(model_name='historicalproposal', name='video_url', field=models.URLField(blank=True, default='', help_text='Short 1-2 min video describing your talk')), migrations.AlterField(model_name='... |
def test_feature_all_scenarios(mocker):
feature = Feature(1, 'Feature', 'I am a feature', 'foo.feature', 1, tags=None)
feature.scenarios.extend([mocker.MagicMock(id=1), mocker.MagicMock(id=2)])
feature.scenarios.append(mocker.MagicMock(spec=ScenarioOutline, id=3, scenarios=[mocker.MagicMock(id=4), mocker.Ma... |
class CORALRegularizer(Regularizer):
def __init__(self, l=1):
self.uses_learning_phase = 1
self.l = l
def set_layer(self, layer):
self.layer = layer
def __call__(self, loss):
if (not hasattr(self, 'layer')):
raise Exception('Need to call `set_layer` on ActivityReg... |
def decimal_to_binary(decimal_val, max_num_digits=20, fractional_part_only=False):
decimal_val_fractional_part = abs((decimal_val - int(decimal_val)))
current_binary_position_val = (1 / 2)
binary_fractional_part_digits = []
while ((decimal_val_fractional_part >= 0) and (len(binary_fractional_part_digits... |
def rtn_sprintf(se: 'SymbolicExecutor', pstate: 'ProcessState'):
logger.debug('sprintf hooked')
buff = pstate.get_argument_value(0)
arg0 = pstate.get_argument_value(1)
try:
arg0f = pstate.get_format_string(arg0)
nbArgs = arg0f.count('{')
args = pstate.get_format_arguments(arg0, [... |
def test_horovod_example(start_ray_client_server_2_cpus):
assert ray.util.client.ray.is_connected()
from ray_lightning.examples.ray_horovod_example import train_mnist
data_dir = os.path.join(tempfile.gettempdir(), 'mnist_data_')
config = {'layer_1': 32, 'layer_2': 64, 'lr': 0.1, 'batch_size': 32}
tr... |
class CommonBaseTesting(CommonBase):
def __init__(self, parent, id=None, *args, **kwargs):
if ('test' in kwargs):
self.test = kwargs.pop('test')
super().__init__(*args, **kwargs)
self.parent = parent
self.id = id
self.args = args
self.kwargs = kwargs
d... |
class Simple_Header_TestCase(ParserTest):
def __init__(self, *args, **kwargs):
ParserTest.__init__(self, *args, **kwargs)
self.ks = '\n%pre-install --interpreter /usr/bin/python --erroronfail --log=/tmp/blah\nls /tmp\n%end\n'
def runTest(self):
self.parser.readKickstartFromString(self.ks... |
def get_cql_models(app, connection=None, keyspace=None):
from .models import DjangoCassandraModel
models = []
single_cassandra_connection = (len(list(get_cassandra_connections())) == 1)
is_default_connection = ((connection == DEFAULT_DB_ALIAS) or single_cassandra_connection)
for (name, obj) in inspe... |
class KeywordProbInferenceDataset(InferenceDataset):
def __init__(self, features: Dict, transforms: Dict, keyword_prob: str, load_into_mem: bool=False, audio_ids: List=None, threshold: Union[(float, str)]=None):
super().__init__(features, transforms, load_into_mem=load_into_mem, audio_ids=audio_ids)
... |
class Decoder(nn.Module):
def __init__(self, d_model, d_ff, d_k, d_v, n_layers, n_heads, len_q):
super(Decoder, self).__init__()
self.layers = nn.ModuleList([DecoderLayer(d_model, d_ff, d_k, d_v, n_heads, len_q) for _ in range(n_layers)])
def forward(self, dec_inputs, enc_outputs):
dec_o... |
def error_description(error_code):
err_message = {'notLink': "Check the 'link' parameter (Empty or bad)", 'notDebrid': 'Maybe the filehoster is down or the link is not online', 'badFileUrl': 'The link format is not valid', 'hostNotValid': 'The filehoster is not supported', 'notFreeHost': 'This filehoster is not ava... |
class Observer():
def __init__(self):
self.id = rpc.get_worker_info().id
self.env = gym.make('CartPole-v1')
self.env.reset(seed=args.seed)
def run_episode(self, agent_rref, n_steps):
(state, ep_reward) = (self.env.reset()[0], 0)
for step in range(n_steps):
act... |
def tscore(sample1, sample2):
if (len(sample1) != len(sample2)):
raise ValueError('different number of values')
error = (pooled_sample_variance(sample1, sample2) / len(sample1))
diff = (statistics.mean(sample1) - statistics.mean(sample2))
return (diff / math.sqrt((error * 2))) |
class CapturableArgumentParser(argparse.ArgumentParser):
def __init__(self, *args: Any, **kwargs: Any) -> None:
self.stdout = kwargs.pop('stdout', sys.stdout)
self.stderr = kwargs.pop('stderr', sys.stderr)
super().__init__(*args, **kwargs)
def print_usage(self, file: (IO[str] | None)=Non... |
.usefixtures('repo_with_no_tags_angular_commits')
def test_errors_when_config_file_invalid_configuration(cli_runner: 'CliRunner', update_pyproject_toml: 'UpdatePyprojectTomlFn'):
update_pyproject_toml('tool.semantic_release.remote.type', 'invalidType')
result = cli_runner.invoke(main, ['--config', 'pyproject.to... |
class ReadHoldingRegistersRequest(ReadRegistersRequestBase):
function_code = 3
function_code_name = 'read_holding_registers'
def __init__(self, address=None, count=None, slave=0, **kwargs):
super().__init__(address, count, slave, **kwargs)
def execute(self, context):
if (not (1 <= self.c... |
.end_to_end()
.parametrize('flag', ['-e', '--exclude'])
.parametrize('pattern', ['*_1.txt', 'to_be_deleted_file_[1]*'])
def test_clean_with_excluded_file_via_config(project, runner, flag, pattern):
project.joinpath('pyproject.toml').write_text(f'''[tool.pytask.ini_options]
exclude = [{pattern!r}]''')
result = r... |
class AutoencoderTinyBlock(nn.Module):
def __init__(self, in_channels: int, out_channels: int, act_fn: str):
super().__init__()
act_fn = get_activation(act_fn)
self.conv = nn.Sequential(nn.Conv2d(in_channels, out_channels, kernel_size=3, padding=1), act_fn, nn.Conv2d(out_channels, out_channe... |
class SKOptLearner(Optimizer, BaseLearner):
def __init__(self, function, **kwargs):
self.function = function
self.pending_points = set()
self.data = collections.OrderedDict()
self._kwargs = kwargs
super().__init__(**kwargs)
def new(self) -> SKOptLearner:
return SK... |
class PoseResNet(nn.Module):
def __init__(self, block, layers, cfg, **kwargs):
self.inplanes = 64
self.deconv_with_bias = cfg.POSE_RESNET.DECONV_WITH_BIAS
self.input_channels = (kwargs['input_channels'] if ('input_channels' in kwargs) else cfg.POSE_RESNET.INPUT_CHANNELS)
self.keep_sc... |
class Battleship(commands.Cog):
def __init__(self, bot: Bot):
self.bot = bot
self.games: list[Game] = []
self.waiting: list[discord.Member] = []
def predicate(self, ctx: commands.Context, announcement: discord.Message, reaction: discord.Reaction, user: discord.Member) -> bool:
if... |
class TestEncodedId():
def test_init_str(self):
obj = utils.EncodedId('Hello')
assert ('Hello' == obj)
assert ('Hello' == str(obj))
assert ('Hello' == f'{obj}')
assert isinstance(obj, utils.EncodedId)
obj = utils.EncodedId('this/is a/path')
assert ('this%2Fis%... |
class Solution(object):
def getSum(self, a, b):
import ctypes
sum = 0
carry = ctypes.c_int32(b)
while (carry.value != 0):
sum = (a ^ carry.value)
carry = ctypes.c_int32((a & carry.value))
carry.value <<= 1
a = sum
return sum |
class Softplus(UnaryScalarOp):
def static_impl(x):
not_int8 = (str(getattr(x, 'dtype', '')) not in ('int8', 'uint8'))
if (x < (- 37.0)):
return (np.exp(x) if not_int8 else np.exp(x, signature='f'))
elif (x < 18.0):
return (np.log1p(np.exp(x)) if not_int8 else np.log1p... |
def test_a_decorated_singleton_should_not_override_a_child_provider():
parent_injector = Injector()
provided_instance = SingletonB()
class MyModule(Module):
def provide_name(self) -> SingletonB:
return provided_instance
child_injector = parent_injector.create_child_injector([MyModule... |
def make_reader():
field_names = None
def read_line(line):
nonlocal field_names
print('\t\t\t\t\t', line)
reader = csv.reader([line])
row = next(reader)
if (field_names is None):
field_names = row
return None
return dict(zip(field_names, ro... |
def test__symmetrical_torque_driven_ocp__symmetry_by_constraint():
from bioptim.examples.symmetrical_torque_driven_ocp import symmetry_by_constraint as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(biorbd_model_path=(bioptim_folder + '/models/cubeSym.bioMod'), phase... |
class Zabbix():
def __init__(self, server, user, password, verify=True):
self.server = server
self.user = user
self.password = password
s = requests.Session()
s.auth = (user, password)
self.zapi = ZabbixAPI(server, s)
self.zapi.session.verify = verify
... |
class SawyerDoorCloseEnvV2(SawyerDoorEnvV2):
def __init__(self):
goal_low = (0.2, 0.65, 0.1499)
goal_high = (0.3, 0.75, 0.1501)
super().__init__()
self.init_config = {'obj_init_angle': 0.3, 'obj_init_pos': np.array([0.1, 0.95, 0.15], dtype=np.float32), 'hand_init_pos': np.array([(- 0... |
def get_dependency_urls(package_name, dependency_list_file):
url_delimiter = '-f '
dependency_file_full_path = prepend_bin_path(package_name, dependency_list_file)
dependency_list_array = open(dependency_file_full_path).read().splitlines()
dependency_urls_list = []
for dependency_line in dependency_... |
class LoggingPlugin():
def __init__(self, config: Config) -> None:
self._config = config
self.formatter = self._create_formatter(get_option_ini(config, 'log_format'), get_option_ini(config, 'log_date_format'), get_option_ini(config, 'log_auto_indent'))
self.log_level = get_log_level_for_sett... |
def check_improper_torsion(improper: Tuple[(int, int, int, int)], molecule: 'Ligand') -> Tuple[(int, int, int, int)]:
for atom_index in improper:
try:
atom = molecule.atoms[atom_index]
bonded_atoms = set()
for bonded in atom.bonds:
bonded_atoms.add(bonded)... |
def preprocess_bilingual_corpora(args: argparse.Namespace, source_dict: Dictionary, char_source_dict: Optional[Dictionary], target_dict: Dictionary, char_target_dict: Optional[Dictionary]):
embed_bytes = getattr(args, 'embed_bytes', False)
if args.train_source_text_file:
args.train_source_binary_path = ... |
class BridgeTowerImageProcessingTester(unittest.TestCase):
def __init__(self, parent, do_resize: bool=True, size: Dict[(str, int)]=None, size_divisor: int=32, do_rescale: bool=True, rescale_factor: Union[(int, float)]=(1 / 255), do_normalize: bool=True, do_center_crop: bool=True, image_mean: Optional[Union[(float, ... |
class HotpotStratifiedBinaryQuestionParagraphPairsDataset(QuestionAndParagraphsDataset):
def __init__(self, questions: List[HotpotQuestion], batcher: ListBatcher, fixed_dataset=False, sample_seed=18, add_gold_distractor=True):
self.questions = questions
self.batcher = batcher
self.fixed_data... |
class CrowdCounter(nn.Module):
def __init__(self, gpus, model_name, pretrained=True):
super(CrowdCounter, self).__init__()
if (model_name == 'CSRNet_LCM'):
from .SCC_Model.CSRNet_LCM import CSRNet_LCM as net
elif (model_name == 'VGG16_LCM'):
from .SCC_Model.VGG16_LCM ... |
class FeatureDictNet(nn.ModuleDict):
def __init__(self, model, out_indices=(0, 1, 2, 3, 4), out_map=None, feature_concat=False, flatten_sequential=False):
super(FeatureDictNet, self).__init__()
self.feature_info = _get_feature_info(model, out_indices)
self.concat = feature_concat
sel... |
def find_resource_info_with_id(info_list: typing.Sequence[T], short_name: str, resource_type: ResourceType) -> T:
for info in info_list:
if (info.short_name == short_name):
return info
raise MissingResource(f"{resource_type.name} Resource with short_name '{short_name}' not found in {len(info... |
class Subset(torch.utils.data.Dataset):
def __init__(self, dataset, indices):
self.dataset = dataset
self.indices = indices
self.group_array = self.get_group_array(re_evaluate=True)
self.label_array = self.get_label_array(re_evaluate=True)
def __getitem__(self, idx):
retu... |
class GroupAttention(nn.Module):
def __init__(self, d_model, dropout=0.8, no_cuda=False):
super(GroupAttention, self).__init__()
self.d_model = 256.0
self.linear_key = nn.Linear(d_model, d_model)
self.linear_query = nn.Linear(d_model, d_model)
self.norm = LayerNorm(d_model)
... |
class StateFieldProperty(object):
def __init__(self, field, parent_property):
self.field = field
self.parent_property = parent_property
def __get__(self, instance, owner):
if instance:
if (self.parent_property and hasattr(self.parent_property, '__get__')):
ret... |
class ESRGAN_model():
def __init__(self, lr_shape, hr_shape, SCALE=4):
self.SCALE = SCALE
(self.lr_shape, self.hr_shape) = (lr_shape, hr_shape)
(self.lr_height, self.lr_width, self.channels) = lr_shape
(self.hr_height, self.hr_width, _) = hr_shape
self.n_residual_in_residual_... |
def _configure_optimizer(learning_rate):
if (FLAGS.optimizer == 'adadelta'):
optimizer = tf.train.AdadeltaOptimizer(learning_rate, rho=FLAGS.adadelta_rho, epsilon=FLAGS.opt_epsilon)
elif (FLAGS.optimizer == 'adagrad'):
optimizer = tf.train.AdagradOptimizer(learning_rate, initial_accumulator_valu... |
.parametrize('ip, host', [('127.0.0.1', 'localhost'), ('27.0.0.1', 'localhost.localdomain'), ('27.0.0.1', 'local'), ('55.255.255.255', 'broadcasthost'), (':1', 'localhost'), (':1', 'ip6-localhost'), (':1', 'ip6-loopback'), ('e80::1%lo0', 'localhost'), ('f00::0', 'ip6-localnet'), ('f00::0', 'ip6-mcastprefix'), ('f02::1'... |
class TestRowAppendableArray(unittest.TestCase):
def test_append_1d_arrays_and_trim_remaining_buffer(self):
appendable = RowAppendableArray(7)
appendable.append_row(np.zeros(3))
appendable.append_row(np.ones(3))
self.assertTrue(np.array_equal(appendable.to_array(), np.array([0, 0, 0,... |
class Unfolding_Loss(Loss, ABC):
def __init__(self, window_length, hop_length, **kwargs):
super().__init__()
self.window_length = window_length
self.hop_length = hop_length
def compute(self, model, mixture_signal, target_signal):
target_signal_hat = model.separate(mixture_signal)... |
class BertSmallModel(nn.Module):
def __init__(self, config, train_embedding=False) -> None:
super().__init__()
self.model = Bert(config).to(device)
self.embedding = copy.deepcopy(self.model.get_input_embeddings().requires_grad_(True))
self.model.set_input_embeddings(nn.Sequential())
... |
def torch_persistent_save(obj, f):
if isinstance(f, str):
with PathManager.open(f, 'wb') as h:
torch_persistent_save(obj, h)
return
for i in range(3):
try:
return torch.save(obj, f)
except Exception:
if (i == 2):
logger.error(tr... |
class Attempt(object):
def __init__(self, value, attempt_number, has_exception):
self.value = value
self.attempt_number = attempt_number
self.has_exception = has_exception
def get(self, wrap_exception=False):
if self.has_exception:
if wrap_exception:
r... |
class Command(BaseCommand):
help = 'Run the ML model on the specified URLs. Results are not stored to the database.'
def add_arguments(self, parser):
parser.add_argument('urls', nargs='+', help=_('URL to run against'))
def handle(self, *args, **kwargs):
self.stdout.write((_('Using the model(... |
def extract_multipart_formdata(data):
_temp = []
REGEX_MULTIPART = '(?is)((Content-Disposition[^\\n]+?name\\s*=\\s*[\\"\']?(?P<name>(.*?))[\\"\']?)(?:;\\s*filename=[\\"\']?(?P<filename>(.*?))[\\"\']?)?(?:\\nContent-Type:\\s*(?P<contenttype>(.*?))\\n)?(?:\\s*)?(?P<value>[\\w\\.\\_\\-\\*\\+\\[\\]\\=\\>\\;\\:\\\'\... |
class TestMPM(TestCase):
def test_well_posed(self):
options = {'thermal': 'isothermal', 'working electrode': 'positive'}
model = pybamm.lithium_ion.MPM(options)
model.check_well_posedness()
model = pybamm.lithium_ion.MPM({'working electrode': 'positive'}, build=False)
model.b... |
class BetaIncInv(ScalarOp):
nfunc_spec = ('scipy.special.betaincinv', 3, 1)
def impl(self, a, b, x):
return scipy.special.betaincinv(a, b, x)
def grad(self, inputs, grads):
(a, b, x) = inputs
(gz,) = grads
return [grad_not_implemented(self, 0, a), grad_not_implemented(self, 0... |
class LxFdtDump(gdb.Command):
def __init__(self):
super(LxFdtDump, self).__init__('lx-fdtdump', gdb.COMMAND_DATA, gdb.COMPLETE_FILENAME)
def fdthdr_to_cpu(self, fdt_header):
fdt_header_be = '>IIIIIII'
fdt_header_le = '<IIIIIII'
if (utils.get_target_endianness() == 1):
... |
def download_coco(path, overwrite=False):
_DOWNLOAD_URLS = [(' '10ad623668ab00c62c096f0ed636d6aff41faca5'), (' '8551ee4bb5860311e79dace7e79cb91e432e78b3'), (' '4950dc9d00dbe1c933ee0170fd2a41')]
mkdir(path)
for (url, checksum) in _DOWNLOAD_URLS:
filename = download(url, path=path, overwrite=overwrite... |
def init():
if dist.is_initialized():
return
if ('MASTER_ADDR' not in os.environ):
os.environ['MASTER_ADDR'] = 'localhost'
if ('MASTER_PORT' not in os.environ):
os.environ['MASTER_PORT'] = '29500'
if ('RANK' not in os.environ):
os.environ['RANK'] = '0'
if ('LOCAL_RANK... |
class RotationTransformer():
valid_reps = ['axis_angle', 'euler_angles', 'quaternion', 'rotation_6d', 'matrix']
def __init__(self, from_rep='axis_angle', to_rep='rotation_6d', from_convention=None, to_convention=None):
assert (from_rep != to_rep)
assert (from_rep in self.valid_reps)
asse... |
class PlyData(object):
def __init__(self, elements=[], text=False, byte_order='=', comments=[], obj_info=[]):
if ((byte_order == '=') and (not text)):
byte_order = _native_byte_order
self.byte_order = byte_order
self.text = text
self.comments = list(comments)
self... |
class _ServerCapabilities():
actions: bool
body_markup: bool
body_hyperlinks: bool
kde_origin_name: bool
def from_list(cls, capabilities: List[str]) -> '_ServerCapabilities':
return cls(actions=('actions' in capabilities), body_markup=('body-markup' in capabilities), body_hyperlinks=('body-h... |
class Effect8104(BaseEffect):
type = 'passive'
def handler(fit, src, context, projectionRange, **kwargs):
lvl = src.level
fit.drones.filteredItemIncrease((lambda mod: mod.item.requiresSkill('Salvage Drone Specialization')), 'accessDifficultyBonus', (src.getModifiedItemAttr('specAccessDifficultyB... |
class SlackOAuth2Test(OAuth2Test):
backend_path = 'social_core.backends.slack.SlackOAuth2'
user_data_url = '
access_token_body = json.dumps({'access_token': 'foobar', 'token_type': 'bearer'})
user_data_body = json.dumps({'ok': True, 'user': {'email': '', 'name': 'Foo Bar', 'id': '123456'}, 'team': {'id'... |
def test_inner_call_with_dynamic_argument() -> None:
node = builder.extract_node('\n def f(x):\n return g(x)\n\n def g(y):\n return y + 2\n\n f(1) #\n ')
assert isinstance(node, nodes.NodeNG)
inferred = node.inferred()
assert (len(inferred) == 1)
assert (inferred[0] is Uni... |
class Font(BaseObject, EqNeAttrs):
bold = 0
character_set = 0
colour_index = 0
escapement = 0
family = 0
font_index = 0
height = 0
italic = 0
name = UNICODE_LITERAL('')
struck_out = 0
underline_type = 0
underlined = 0
weight = 400
outline = 0
shadow = 0 |
class DummyCondStage():
def __init__(self, conditional_key):
self.conditional_key = conditional_key
self.train = None
def eval(self):
return self
def encode(c: Tensor):
return (c, None, (None, None, c))
def decode(c: Tensor):
return c
def to_rgb(c: Tensor):
... |
class cifar_dataloader():
def __init__(self, dataset, r, noise_mode, batch_size, num_workers, root_dir, log, noise_file=''):
self.dataset = dataset
self.r = r
self.noise_mode = noise_mode
self.batch_size = batch_size
self.num_workers = num_workers
self.root_dir = root... |
def tags_handler(ctx, param, value):
retval = options.from_like_context(ctx, param, value)
if ((retval is None) and value):
try:
retval = dict((p.split('=') for p in value))
except Exception:
raise click.BadParameter(("'%s' contains a malformed tag." % value), param=param... |
class FlavaImageConfig(PretrainedConfig):
model_type = 'flava_image_model'
def __init__(self, hidden_size: int=768, num_hidden_layers: int=12, num_attention_heads: int=12, intermediate_size: int=3072, hidden_act: int='gelu', hidden_dropout_prob: float=0.0, attention_probs_dropout_prob: float=0.0, initializer_ra... |
class unit_tcn_G(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size=9, stride=1):
super(unit_tcn_G, self).__init__()
pad = int(((kernel_size - 1) / 2))
inter_channels = (out_channels // 4)
self.inter_c = inter_channels
self.conv = nn.Conv2d(in_channels, out... |
class SFTLayer_torch(nn.Module):
def __init__(self):
super(SFTLayer_torch, self).__init__()
self.SFT_scale_conv0 = nn.Conv2d(32, 32, 1)
self.SFT_scale_conv1 = nn.Conv2d(32, 64, 1)
self.SFT_shift_conv0 = nn.Conv2d(32, 32, 1)
self.SFT_shift_conv1 = nn.Conv2d(32, 64, 1)
def ... |
class TextAccumulator():
def __init__(self, separator: str=''):
self._separator = separator
self._texts: List[str] = []
def push(self, text: str) -> None:
self._texts.append(text)
def pop(self) -> Iterator[str]:
if (not self._texts):
return
text = self._se... |
class Decorators(NodeNG):
_astroid_fields = ('nodes',)
nodes: list[NodeNG]
def postinit(self, nodes: list[NodeNG]) -> None:
self.nodes = nodes
def scope(self) -> LocalsDictNodeNG:
if (not self.parent):
raise ParentMissingError(target=self)
if (not self.parent.parent):... |
('bot.constants.Channels.incidents', 123)
class TestIsIncident(unittest.TestCase):
def setUp(self) -> None:
self.incident = MockMessage(channel=MockTextChannel(id=123), content='this is an incident', author=MockUser(bot=False), pinned=False, reference=None)
def test_is_incident_true(self):
self.... |
def test_bound_crs__example():
proj_crs = ProjectedCRS(conversion=TransverseMercatorConversion(latitude_natural_origin=0, longitude_natural_origin=15, false_easting=2520000, false_northing=0, scale_factor_natural_origin=0.9996), geodetic_crs=GeographicCRS(datum=CustomDatum(ellipsoid='International 1924 (Hayford 190... |
def build_valid_col_units(table_units, schema):
col_ids = [table_unit[1] for table_unit in table_units if (table_unit[0] == TABLE_TYPE['table_unit'])]
prefixs = [col_id[:(- 2)] for col_id in col_ids]
valid_col_units = []
for value in schema.idMap.values():
if (('.' in value) and (value[:value.in... |
def main():
opts = TrainOptions().parse()
if os.path.exists(opts.exp_dir):
raise Exception('Oops... {} already exists'.format(opts.exp_dir))
os.makedirs(opts.exp_dir)
opts_dict = vars(opts)
pprint.pprint(opts_dict)
with open(os.path.join(opts.exp_dir, 'opt.json'), 'w') as f:
json... |
def test_fix_finalizer_func_only(testdir):
testdir.makepyfile("\n import time, pytest\n\n class TestFoo:\n\n \n def fix(self, request):\n print('fix setup')\n def fin():\n print('fix finaliser')\n time.sleep(0.1)... |
def test_multiple_channel_states(chain_state, token_network_state, channel_properties):
open_block_number = 10
open_block_hash = factories.make_block_hash()
pseudo_random_generator = random.Random()
(properties, pkey) = channel_properties
channel_state = factories.create(properties)
channel_new_... |
def _list_to_acl(entry_list, map_names=1):
def char_to_acltag(typechar):
if (typechar == 'U'):
return posix1e.ACL_USER_OBJ
elif (typechar == 'u'):
return posix1e.ACL_USER
elif (typechar == 'G'):
return posix1e.ACL_GROUP_OBJ
elif (typechar == 'g'):
... |
def test_example():
parser = ArgumentParser()
action = make_action(nargs=1)
assert (interactive.example(parser, action, {}).strip() == '# --option OPTION')
assert (interactive.example(parser, action, {'option': 32}).strip() == '--option 32')
action = make_action(nargs=3)
example = interactive.ex... |
def test_timeheadwaycondition():
cond = OSC.TimeHeadwayCondition('Ego', 20, OSC.Rule.equalTo, True, False)
prettyprint(cond.get_element())
cond2 = OSC.TimeHeadwayCondition('Ego', 20, OSC.Rule.equalTo, True, False)
cond3 = OSC.TimeHeadwayCondition('Ego', 20, OSC.Rule.equalTo, True, True, routing_algorith... |
def test_jaynes_cummings_zero_temperature_spectral_callable():
N = 10
a = qutip.tensor(qutip.destroy(N), qutip.qeye(2))
sp = qutip.tensor(qutip.qeye(N), qutip.sigmap())
psi0 = qutip.ket2dm(qutip.tensor(qutip.basis(N, 1), qutip.basis(2, 0)))
kappa = 0.05
a_ops = [((a + a.dag()), (lambda w: (kappa... |
class ContextFormatter(ABC):
def get_formatters(self) -> MutableMapping:
def format_path(cls, path: str, modifier: str) -> str:
if (not modifier):
return os.path.normpath(path)
modifiers = modifier.split(':')[::(- 1)]
while (modifiers and (modifiers[(- 1)] == 'parent')):
... |
class DescribeInlineShapes():
def it_knows_how_many_inline_shapes_it_contains(self, inline_shapes_fixture):
(inline_shapes, expected_count) = inline_shapes_fixture
assert (len(inline_shapes) == expected_count)
def it_can_iterate_over_its_InlineShape_instances(self, inline_shapes_fixture):
... |
def get_current_component_version_from_source_files(component: str, version_file: Optional[str]=None) -> str:
all_version_files = get_component_version_files(component, abs_path=True)
if version_file:
all_version_files = {version_file: all_version_files[version_file]}
version = ''
if all_version... |
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